Pharmacotherapeutic treatments are the most common intervention in the treatment of major depressive disorder (MDD). Response rates to the first antidepressant can be as low as 50-60%1 while clinically more meaningful remission rates are typically only between 20%2-35%1. Development of biological tests that would enable clinicians to select the correct class of antidepressant would significantly reduce morbidity and mortality associated with MDD by reducing the time to remission. We propose to evaluate potential biological tests that can predict remission from MDD when treated with a selective serotonin reuptake inhibitor (SSRI) and whether an individual patient is more likely to respond to a SSRI or a selective norepinephrine reuptake inhibitor (SNRI), the 2 most common classes of medication for MDD. We have shown that depressed patients have higher serotonin 1A (5-HT1A) binding potential than controls. Additionally, in a naturalistic treatment study we found MDD patients with higher 5-HT1A binding potential were less likely to remit to community based treatment. It has recently been shown that baseline serotonin transporter (5-HTT) availability in the midbrain, but not striatum3, predicts response to treatment with a SSRI.4 In our naturalistic study we show that remitters have higher 5-HTT binding potential in a regionally specific manner compared to non-remitters. The treatment protocol was not controlled in our pilot study and there were too few patients to determine if remission depended on the class of antidepressant. In this proposal, we propose to perform pretreatment positron emission tomography (PET) scans and have all patients receive a standardized treatment protocol of a SSRI followed by a SNRI in SSRI non-remitters. Escitalopram is the SSRI and desipramine the SNRI of choice because at the doses we will administer, they are highly selective for the respective transporters. We hypothesize that patients with high pre and postsynaptic 5-HT1A binding potential and low 5-HTT binding potential in the midbrain, amygdala, thalamus, and dorsal putamen will not remit to a SSRI and will remit to a SNRI. Finally, we will generate a predictive model of remission based on brain imaging outcome measures. Our overall goal is to reduce the trial and error associated with finding an effective antidepressant by using data from pre-treatment quantification of 5-HT1A receptors and 5-HTT to guide antidepressant treatment selection.